Thameur Portfolio

Fire Detection and Response System 🔥

June 15, 2022 (2y ago)

🔥 A real-time fire detection system powered by a CNN model for classification and a robotic system designed to detect and respond to fires using sensors and actuators.

💻 Source Code  • 
Fire Detection and Response System: Real-Time Monitoring
Fire Detection and Response System: Real-Time Monitoring

📍 Abstract

The Fire Detection and Response System is designed to monitor and respond to fire incidents in real-time. The system leverages a Convolutional Neural Network (CNN) for fire classification and a robotic system equipped with sensors and actuators to detect and act upon fire events. The CNN model is trained to classify images into two categories: "fire" and "no fire." The robotic system is capable of responding to fire detection by activating various components, such as a water pump, buzzer, and robotic arm, to mitigate potential fire hazards.

🌟 Features

  • Real-Time Fire Detection: Detects and classifies fire from live video feeds.
  • CNN Model for Image Classification: Uses a deep learning model for accurate fire detection.
  • Robotic Response System: A robotic arm with sensors and actuators responds to detected fire events.
  • SMS Notification: Sends SMS alerts to users when fire is detected.
  • Customizable Parameters: Adjust the detection thresholds for optimal performance.
  • Ease of Use: Run the Python scripts for both fire detection and robotic response with minimal setup.

🚀 Getting Started

Prerequisites

Before you can run this project, ensure the following packages are installed:

  • TensorFlow
  • Keras
  • OpenCV
  • Twilio
  • Geocoder
  • Raspberry Pi GPIO

Installation

  1. Clone the repository:
git clone https://github.com/verus56/bk-fire.git  
cd fire-detection-system
  1. Install required dependencies:
pip install tensorflow keras opencv-python twilio geocoder
  1. Set up your Raspberry Pi with the necessary sensors (flame, smoke, etc.) and actuators (water pump, buzzer, LED, servo motor).

Running the App

To test the model with the webcam:

python firewithtsms.py

To detect fire and send SMS alerts:

python fire-with-all.py

To run the robotic system:

python robot.py

🤖 How It Works

  1. Fire Detection: The CNN model analyzes the video stream or images to detect fire and classify them.
  2. Robotic System: Once fire is detected, the robotic system is activated to respond using sensors, a water pump, buzzer, and a servo-controlled robotic arm.
  3. SMS Alerts: Twilio is used to send SMS notifications to the designated users when fire is detected.

📊 Technical Stack

  • AI Engine: Convolutional Neural Network (CNN)
  • Image Processing: OpenCV
  • Data Processing: NumPy
  • Robotic System: Raspberry Pi GPIO, Servo Motor, Water Pump
  • Cloud API: Twilio (SMS Alerts)
  • Geocoding: Geocoder

🛠️ Deployment

This system can be deployed on a Raspberry Pi or other compatible hardware for real-time fire detection and response.

📝 License

Released under the MIT License.

📲 Contact

Made with ❤️ by Hamzaoui Thameur